• journal_title：Geophysics
• Contributor：Yanfei Wang ; Changchun Yang
• Publisher：Society of Exploration Geophysicists
• Date：2010-
• Format：text/html
• Language：en
• Identifier：10.1190/1.3457923
• journal_abbrev：Geophysics
• issn：0016-8033
• volume：75
• issue：4
• firstpage：S131
• section：SEISMIC MIGRATION

New solution methods were considered for migration deconvolution in seismic imaging problems. It is well known that direct migration methods, using the adjoint operator , yield a lower-resolution or blurred image, and that the linearized inversion of seismic data for the reflectivity model usually requires solving a (regularized) least-squares migration problem. We observed that the (regularized) least-squares method is computationally expensive, which becomes a severe obstacle for practical applications. Iterative gradient-descent methods were studied and an efficient method for migration deconvolution was developed. The problem was formulated by incorporating regularizing constraints, and then a nonmonotone gradient-descent method was applied to accelerate the convergence. To test the potential of the application of the developed method, synthetic two-dimensional and three-dimensional seismic-migration-deconvolution simulations were performed. Numerical performance indicates that this method is promising for practical seismic migration imaging.